Error bounds for parallel communication channels

Error bounds for parallel communication channel

Error bounds for parallel communication channels.

Bibliography: p. 87-88.Contract no. DA36-039-AMC-03200(E)

Communications in the observation limited regime

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.Cataloged from PDF version of thesis.Includes bibliographical references (p. 141-145).We consider the design of communications systems when the principal cost is observing the channel, as opposed to transmit energy per bit or spectral efficiency. This is motivated by energy constrained communications devices where sampling the signal, rather than transmitting or processing it, dominates energy consumption. We show that sequentially observing samples with the maximum a posteriori entropy can reduce observation costs by close to an order of magnitude using a (24,12) Golay code. This is the highest performance reported over the binary input AWGN channel, with or without feedback, for this blocklength. Sampling signal energy, rather than amplitude, lowers circuit complexity and power dissipation significantly, but makes synchronization harder. We show that while the distance function of this non-linear coding problem is intractable in general, it is Euclidean at vanishing SNRs, and root Euclidean at large SNRs. We present sequences that maximize the error exponent at low SNRs under the peak power constraint, and under all SNRs under an average power constraint. Some of our new sequences are an order of magnitude shorter than those used by the 802.15.4a standard.(cont.) In joint work with P. Mercier and D. Daly, we demonstrate the first energy sampling wireless modem capable of synchronizing to within a ns, while sampling energy at only 32 Msamples per second, and using no high speed clocks. We show that traditional, minimum distance classifiers may be highly sensitive to parameter estimation errors, and propose robust, computationally efficient alternatives. We challenge the prevailing notion that energy samplers must accurately shift phase to synchronize with high precision.by Manish Bhardwaj.Ph.D

Sparse graph codes for compression, sensing, and secrecy

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.Cataloged from student PDF version of thesis.Includes bibliographical references (p. 201-212).Sparse graph codes were first introduced by Gallager over 40 years ago. Over the last two decades, such codes have been the subject of intense research, and capacity approaching sparse graph codes with low complexity encoding and decoding algorithms have been designed for many channels. Motivated by the success of sparse graph codes for channel coding, we explore the use of sparse graph codes for four other problems related to compression, sensing, and security. First, we construct locally encodable and decodable source codes for a simple class of sources. Local encodability refers to the property that when the original source data changes slightly, the compression produced by the source code can be updated easily. Local decodability refers to the property that a single source symbol can be recovered without having to decode the entire source block. Second, we analyze a simple message-passing algorithm for compressed sensing recovery, and show that our algorithm provides a nontrivial f1/f1 guarantee. We also show that very sparse matrices and matrices whose entries must be either 0 or 1 have poor performance with respect to the restricted isometry property for the f2 norm. Third, we analyze the performance of a special class of sparse graph codes, LDPC codes, for the problem of quantizing a uniformly random bit string under Hamming distortion. We show that LDPC codes can come arbitrarily close to the rate-distortion bound using an optimal quantizer. This is a special case of a general result showing a duality between lossy source coding and channel coding-if we ignore computational complexity, then good channel codes are automatically good lossy source codes. We also prove a lower bound on the average degree of vertices in an LDPC code as a function of the gap to the rate-distortion bound. Finally, we construct efficient, capacity-achieving codes for the wiretap channel, a model of communication that allows one to provide information-theoretic, rather than computational, security guarantees. Our main results include the introduction of a new security critertion which is an information-theoretic analog of semantic security, the construction of capacity-achieving codes possessing strong security with nearly linear time encoding and decoding algorithms for any degraded wiretap channel, and the construction of capacity-achieving codes possessing semantic security with linear time encoding and decoding algorithms for erasure wiretap channels. Our analysis relies on a relatively small set of tools. One tool is density evolution, a powerful method for analyzing the behavior of message-passing algorithms on long, random sparse graph codes. Another concept we use extensively is the notion of an expander graph. Expander graphs have powerful properties that allow us to prove adversarial, rather than probabilistic, guarantees for message-passing algorithms. Expander graphs are also useful in the context of the wiretap channel because they provide a method for constructing randomness extractors. Finally, we use several well-known isoperimetric inequalities (Harper's inequality, Azuma's inequality, and the Gaussian Isoperimetric inequality) in our analysis of the duality between lossy source coding and channel coding.by Venkat Bala Chandar.Ph.D

MMSE equalizers and precoders in turbo equalization.

Thesis (M.Sc.Eng.)-University of Natal, Durban, 2003.Transmission of digital information through a wireless channel with resolvable multipaths or a bandwidth limited channel results in intersymbol interference (1SI) among a number of adjacent symbols. The design of an equalizer is thus important to combat the ISI problem for these types of channels and hence provides reliable communication. Channel coding is used to provide reliable data transmission by adding controlled redundancy to the data. Turbo equalization (TE) is the joint design of channel coding and equalization to approach the achievable uniform input information rate of an ISI channel. The main focus of this dissertation is to investigate the different TE techniques used for a static frequency selective additive white Gaussian noise (AWGN) channel. The extrinsic information transfer (EXIT) chart is used to analyse the iterative equalization/decoding process and to determine the minimum signal to noise ratio (SNR) in order to achieve convergence. The use of the Minimum Mean Square Error (MMSE) Linear Equalizer (LE) using a priori information has been shown to achieve the same performance compared with the optimal trellis based Maximum A Posterior (MAP) equalizer for long block lengths. Motivated by improving the performance of the MMSE LE, two equalization schemes are initially proposed: the MMSE Linear Equalizer with Extrinsic information Feedback (LE-EF (1) and (U)). A general structure for the MMSE LE, MMSE Decision Feedback Equalizer (DFE) and two MMSE LE-EF receivers, using a priori information is also presented. The EXIT chart is used to analyse the two proposed equalizers and their characteristics are compared to the existing MAP equalizer, MMSE LE and MMSE DFE. It is shown that the proposed MMSE LE-EF (1) does have an improved performance compared with the existing MMSE LE and approaches the MMSE Linear Equalizer with Perfect Extrinsic information Feedback (LE-PEF) only after a large number of iterations. For this reason the MMSE LE-EF is shown to suffer from the error propagation problem during the early iterations. A novel way to reduce the error propagation problem is proposed to further improve the performance of the MMSE LE-EF (I). The MAP equalizer was shown to offer a much improved performance over the MMSE equalizers, especially during the initial iterations. Motivated by using the good quality of the MAP equalizer during the early iterations and the hybrid MAP/MMSE LE-EF (l) is proposed in order to suppress the error propagation problem inherent in the MMSE LE-EF (I). The EXIT chart analysis reveals that the hybrid MAP/MMSE LE-EF (l) requires fewer iterations in order to achieve convergence relative to the MMSE LE-EF (l). Simulation results demonstrate that the hybrid MAP/MMSE LE-EF (I) has a superior performance compared to the MMSE LE-EF (I) as well as approaches the performance of both the MAP equalizer and MMSE LE-PEF at high SNRs, at the cost of increased complexity relative to the MMSE LEEF (I) receiver. The final part of this dissertation considers the use of precoders in a TE system. It was shown in the literature that a precoder drastically improves the system performance. Motivated by this, the EXIT chart is used to analyse the characteristics of four different precoders for long block lengths. It was shown that using a precoder results in a loss in mutual information during the initial equalization stage. However" we show by analysis and simulations that this phenomenon is not observed in the equalization of all precoded channels. The slope of the transfer function, relating to the MAP equalization of a precoded ISI channel (MEP), during the high input mutual information values is shown to play an important role in determining the convergence of precoded TE systems. Simulation results are presented to show how the precoders' weight affects the convergence of TE systems. The design of the hybrid MAP/MEP equalizer is also proposed. We also show that the EXIT chart can be used to compute the trellis code capacity of a precoded ISI channel

Partially Coupled Codes for TB-based Transmission

In this thesis, we mainly investigate the design of partially coupled codes for transport block (TB) based transmission protocol adopted in 4G/5G mobile network standards. In this protocol, an information sequence in a TB is segmented into multiple code blocks (CBs) and each CB is protected by a channel codeword independently. It is inefficient in terms of transmit power and spectrum efficiency because any erroneous CB in a TB leads to the retransmission of the whole TB. An important research problem related to this TB-based transmission is how to improve the TB error rate (TBER) performance so that the number of retransmissions reduces. To tackle this challenge, we present a class of spatial coupling techniques called partial coupling in the TB encoding operation, which has two subclasses: partial information coupled (PIC) and partial parity coupling (PPC). To be specific, the coupling is performed such that a fraction of the information/parity sequence of one component code at the current CB is used as the input of the component encoder at the next CB, leading to improved TBER performance. One of the appealing features of partial coupling (both PIC and PPC) is that the coupling can be applied to any component codes without changing their encoding and decoding architectures, making them compatible with the TB-based transmission protocol. The main body of this thesis consists of two parts. In the first part, we apply both PIC and PPC to turbo codes. We investigate various coupling designs and analysis the performance of the partially coupled turbo codes over the binary erasure channel via density evolution (DE). Both simulation results and DE analysis show that such a class of codes can approach channel capacity with a large blocklength. In the second part, we construct PIC-polar codes. We show that PIC can effectively improve the error performance of finite-length polar codes by utilizing the channel polarization phenomenon. The DE-based performance analysis is also conducted. For both turbo codes and polar codes, we have shown that the partially coupled codes have significant performance gain over their uncoupled counterpart, demonstrating the effectiveness of the partial coupling

A framework for low-complexity communication over channels with feedback

"November 1997."Also issued as Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of electrical Engineering and Computer Science, 1997.Includes bibliographical references (p. 181-185).Supported in part by the Advanced Research Projects Agency. N00014-93-1-0686 Supported in part by the U.S. Department of the Navy, Office of Naval Research. N00014-96-10930 Supported by an AT&Tdoctoral fellowshipJames M. Ooi